Added pure vs non pure hit and run examples

examples/Fragmentation/Fragmentation_Movie.py

@@ -36,8 +36,8 @@
 # ----------------------------------------------------------------------------------------------------------------------
 # Define the names and initial conditions of the various fragmentation simulation types
 # ----------------------------------------------------------------------------------------------------------------------
-available_movie_styles = ["disruption_headon", "disruption_off_axis", "supercatastrophic_headon", "supercatastrophic_off_axis","hitandrun"]
-movie_title_list = ["Head-on Disruption", "Off-axis Disruption", "Head-on Supercatastrophic", "Off-axis Supercatastrophic", "Hit and Run"]
+available_movie_styles = ["disruption_headon", "disruption_off_axis", "supercatastrophic_headon", "supercatastrophic_off_axis","hitandrun_disrupt", "hitandrun_pure"]
+movie_title_list = ["Head-on Disruption", "Off-axis Disruption", "Head-on Supercatastrophic", "Off-axis Supercatastrophic", "Hit and Run w/ Runner Disruption", "Pure Hit and Run"]
 movie_titles = dict(zip(available_movie_styles, movie_title_list))
 
 # These initial conditions were generated by trial and error
@@ -50,8 +50,10 @@
                                               np.array([1.0,  5.0e-05, 0.0])],
                "supercatastrophic_off_axis": [np.array([1.0, -5.0e-05, 0.0]),
                                               np.array([1.0,  5.0e-05, 0.0])],
-               "hitandrun"                 : [np.array([1.0, -4.2e-05, 0.0]),
-                                              np.array([1.0,  4.2e-05, 0.0])]
+               "hitandrun_disrupt"         : [np.array([1.0, -4.2e-05, 0.0]),
+                                              np.array([1.0,  4.2e-05, 0.0])],
+               "hitandrun_pure"            : [np.array([1.0, -4.2e-05, 0.0]),
+                                              np.array([1.0,  4.2e-05, 0.0])] 
                }
 
 vel_vectors = {"disruption_headon"         : [np.array([ 0.00,  6.280005, 0.0]),
@@ -62,8 +64,10 @@
                                               np.array([ 0.00, -6.28,     0.0])],
                "supercatastrophic_off_axis": [np.array([ 0.00,  6.28,     0.0]),
                                               np.array([ 0.50, -6.28,     0.0])],
-               "hitandrun"                 : [np.array([ 0.00,  6.28,     0.0]),
-                                              np.array([-1.45, -6.28,     0.0])]
+               "hitandrun_disrupt"         : [np.array([ 0.00,  6.28,     0.0]),
+                                              np.array([-1.45, -6.28,     0.0])],
+               "hitandrun_pure"            : [np.array([ 0.00,  6.28,     0.0]),
+                                              np.array([-1.50, -6.28,     0.0])]
                }
 
 rot_vectors = {"disruption_headon"         : [np.array([0.0, 0.0, 0.0]),
@@ -74,15 +78,18 @@
                                               np.array([0.0, 0.0, 0.0])],
                "supercatastrophic_off_axis": [np.array([0.0, 0.0, -6.0e4]),
                                               np.array([0.0, 0.0, 1.0e5])],
-               "hitandrun"                 : [np.array([0.0, 0.0, 6.0e4]),
+               "hitandrun_disrupt"         : [np.array([0.0, 0.0, 6.0e4]),
+                                              np.array([0.0, 0.0, 1.0e5])],
+               "hitandrun_pure"            : [np.array([0.0, 0.0, 6.0e4]),
                                               np.array([0.0, 0.0, 1.0e5])]
                }
 
 body_Gmass = {"disruption_headon"        : [1e-7, 1e-10],
              "disruption_off_axis"       : [1e-7, 1e-10],
              "supercatastrophic_headon": [1e-7, 1e-8],
              "supercatastrophic_off_axis": [1e-7, 1e-8],
-             "hitandrun"                 : [1e-7, 7e-10]
+             "hitandrun_disrupt"         : [1e-7, 7e-10],
+             "hitandrun_pure"            : [1e-7, 7e-10]
                }
 
 density = 3000 * swiftest.AU2M**3 / swiftest.MSun
@@ -91,7 +98,8 @@
 for k,v in body_Gmass.items():
     body_radius[k] = [((Gmass/GU)/(4./3.*np.pi*density))**(1./3.) for Gmass in v]
 
-body_radius["hitandrun"] = [7e-6, 3.25e-6] 
+body_radius["hitandrun_disrupt"] = [7e-6, 3.25e-6] 
+body_radius["hitandrun_pure"] = [7e-6, 3.25e-6] 
 
 # ----------------------------------------------------------------------------------------------------------------------
 # Define the animation class that will generate the movies of the fragmentation outcomes
@@ -202,17 +210,19 @@ def data_stream(self, frame=0):
     print("2. Off-axis disruption")
     print("3. Head-on supercatastrophic")
     print("4. Off-axis supercatastrophic")
-    print("5. Hit and run")
-    print("6. All of the above")
+    print("5. Hit and run with disruption of the runner")
+    print("6. Pure hit and run")
+    print("7. All of the above")
     user_selection = int(input("? "))
 
-    if user_selection > 0 and user_selection < 6:
+    if user_selection > 0 and user_selection < 7:
         movie_styles = [available_movie_styles[user_selection-1]]
     else:
         print("Generating all movie styles")
         movie_styles = available_movie_styles.copy()
 
     for style in movie_styles:
+        print(f"Generating {movie_titles[style]}")
         movie_filename = f"{style}.mp4"
         # Pull in the Swiftest output data from the parameter file and store it as a Xarray dataset.
         sim = swiftest.Simulation(simdir=style, rotation=True, init_cond_format = "XV", compute_conservation_values=True)